Open benjamin3344 opened 2 years ago
Can someone explain to me what are the approximate dimensions of latent embedding for different datasets? For the following procedure:
origin_img -> [encoder] -> latent -> [diffuse] -> noise -> [reverse diffuse]-> latent -> [decoder] -> recon_img
ps: do you think it will still make sense to use diffusion models for a low-dimensional latent space? e.g. 10 or 20.
Can someone explain to me what are the approximate dimensions of latent embedding for different datasets? For the following procedure:
origin_img -> [encoder] -> latent -> [diffuse] -> noise -> [reverse diffuse]-> latent -> [decoder] -> recon_img
ps: do you think it will still make sense to use diffusion models for a low-dimensional latent space? e.g. 10 or 20.